Images captured on film or by electronic devices such as scanners and television cameras are often corrupted with noise. In the case of images captured on film, the noise is introduced by grains in the photographic emulsions. In the case of cameras for use with video recorders, the CCD arrays are known to introduce a significant amount of noise. Other sources of noise may also affect both still and motion picture images.
A number of methods of removing noise from images are known to the art. These can be divided into linear and non-linear filtering techniques. In a linear filtering technique a pixel in an image is replaced by a weighted sum of nearby pixels. An isolated pixel value generated by a noise event will be altered to a value that is nearer to that of the nearby pixels when this averaging operation is applied; hence, the noise is reduced. Unfortunately, this type of filter also blurs edges that are not generated by noise. Hence, overall picture quality is reduced as well.
Non-linear methods, in principle, can remove noise without significantly altering the overall picture quality. For example, U.S. Pat. No. 5,010,504 to Lee et al. describes a non-linear method based on the Singular Value Decomposition ("SVD") block transform of a difference image to provide an image having reduced noise. In the method taught by Lee et al., the image is first filtered using a conventional linear lowpass filter to generate a smoothed image. The smoothed image is subtracted from the original image to generate a difference image. The difference image is then processed to remove noise. The processed difference image is then added to the smoothed image to provide the final filtered image.
The difference image is processed by (1) dividing the difference image into blocks and (2) transforming each block via the SVD block transform. Let the original block be denoted by H: EQU H=UDV.sup.T (1)
where U and V are orthogonal matrices and D is a diagonal matrix. The transform involves changing some of the values of D to obtain a new diagonal matrix D'. This new matrix is then substituted for D in Eq. (1) to generate the block to be used in the processed difference image.
In the system taught by Lee et al., the alterations made to D depend on a knowledge of the statistical properties of the noise. To obtain this knowledge, a region of the image that consists entirely of noise must be identified. The pixels of this region can then be used to generate the required statistical information. This process requires human intervention to identify the regions having only noise; hence, the method is poorly suited to automatic noise reduction of the type that would be useful in scanners or other image capture systems.
In addition, the method taught by Lee et al. assumes that the noise statistics in the regions of the image having non-noise information are the same as those in the region having only noise. This is not necessarily true for all capture devices. For example, vidicon cameras do not satisfy this constraint.
Prior art methods do not provide any automatic method for setting the parameters of the noise reduction algorithm absent some form of human intervention. As noted above, the method taught by Lee et al. requires the user to identify a region which is essentially all noise pixels so that the algorithm can compute the required statistics needed to alter the values in D. Methods in which a user views the filtered image to determine if it requires additional noise reduction or has suffered significant image degradation are also known to the art.
Broadly, it is an object of the invention to provide an improved image noise filter and an improved method of filtering noise from images.
It is another object of the invention to provide an image noise filter and filtering method that operates without human intervention.
It is another object of the invention to provide a image noise filter and filtering method that does not significantly degrade the image.
These and other objects of the invention will become apparent to those skilled in the art from the following detailed description of the invention and the accompanying drawings.